scholarly journals Volcanic Anomalies Monitoring System (VOLCANOMS), a Low-Cost Volcanic Monitoring System Based on Landsat Images

2020 ◽  
Vol 12 (10) ◽  
pp. 1589 ◽  
Author(s):  
Susana Layana ◽  
Felipe Aguilera ◽  
Germán Rojo ◽  
Álvaro Vergara ◽  
Pablo Salazar ◽  
...  
Keyword(s):  
Monitoring System ◽  
Seismic Data ◽  
Near Infrared ◽  
Landsat Imagery ◽  
Low Cost ◽  
Short Wave ◽  
Eruptive Activity ◽  
Landsat Images ◽  
Thermal Anomalies ◽  
Volcanic Monitoring

The practice of monitoring active volcanoes, includes several techniques using either direct or remote measurements, the latter being more important for volcanoes with limited accessibility. We present the Volcanic Anomalies Monitoring System (VOLCANOMS), a new, online, low-cost and semiautomatic system based on Landsat imagery. This system can detect permanent and/or temporal thermal anomalies in near-infrared (NIR), short-wave infrared (SWIR), and thermal infrared (TIR) bands. VOLCANOMS allows researchers to calculate several thermal parameters, such as thermal radiance, effective temperature, anomaly area, radiative, gas, convective, and total heat, and mass fluxes. We study the eruptive activity of five volcanoes including Krakatau, Stromboli, Fuego, Villarrica and Lascar volcanoes, comparing field and eruptive data with thermal radiance. In the case of Villarrica and Lascar volcanoes, we also compare the thermal radiance and eruptive activity with seismic data. The thermal radiance shows a concordance with the eruptive activity in all cases, whereas a correlation is observed between thermal and seismic data both, in Villarrica and Lascar volcanoes, especially in the case of long-period seismicity. VOLCANOMS is a new and powerful tool that, combined with other techniques, generates robust information for volcanic monitoring.

scholarly journals Lithological mapping of East Tianshan area using integrated data fused by Chinese GF-1 PAN and ASTER multi-spectral data

2018 ◽  
Vol 10 (1) ◽  
pp. 532-543 ◽  
Author(s):  
Min Yang ◽  
Lei Kang ◽  
Huaqing Chen ◽  
Min Zhou ◽  
Jianghua Zhang
Keyword(s):  
Spectral Resolution ◽  
Near Infrared ◽  
Thermal Emission ◽  
Low Cost ◽  
Short Wave ◽  
Support Vector ◽  
Tianshan Mountain ◽  
Multispectral Data ◽  
Fusion Data ◽  
East Tianshan

Abstract The East Tianshan Mountain is one of the most important gold ore forming zones in northwestern China and central Asia. The Chinese GaoFen-1 (GF-1), the first Chinese high resolution satellite, is characterized by its 2-m resolution PAN data. The Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER), the well-known earth observation satellite, is advanced by its finer spectral resolution owing 9 bands in the visible and near infrared (VNIR) to the short-wave infrared (SWIR) region. In this study, we fused the GF-1 PAN and the ASTER multispectral data using the well-known Gram-Schmidt Pan Sharpening (G-S) method to produce a new data with both high spatial and spectral resolution. Then different lithological units were mapped respectively using the fusion data, the ASTER data and the WorldView-3 data by support vector machine (SVM) method. In order to assess this fusion data, a comparison work was executed among the three mapping results. The comparison work indicated that lithological classification using the new fusion data is an efficient, robust and low cost method, and it could replace the WV-3 data in some large sale geological work.

scholarly journals A COMPARISON OF HAZE REMOVAL ALGORITHMS AND THEIR IMPACTS ON CLASSIFICATION ACCURACY FOR LANDSAT IMAGERY

2017 ◽  
Vol 23 (1) ◽  
pp. 55-71 ◽  
Author(s):  
Yang Xiao ◽  
Zhiyun Ouyang ◽  
Zhiming Zhang ◽  
Chaofan Xian
Keyword(s):  
Classification Accuracy ◽  
Near Infrared ◽  
Landsat Imagery ◽  
Spectral Response ◽  
Landsat Images ◽  
Haze Removal ◽  
Reference Images ◽  
The Difference ◽  
Spatially Varying

The quality of Landsat images in humid areas is considerably degraded by haze in terms of their spectral response pattern, which limits the possibility of their application in using visible and near-infrared bands. A variety of haze removal algorithms have been proposed to correct these unsatisfactory illumination effects caused by the haze contamination. The purpose of this study was to illustrate the difference of two major algorithms (the improved homomorphic filtering (HF) and the virtual cloud point (VCP)) for their effectiveness in solving spatially varying haze contamination, and to evaluate the impacts of haze removal on land cover classification. A case study with exploiting large quantities of Landsat TM images and climates (clear and haze) in the most humid areas in China proved that these haze removal algorithms both perform well in processing Landsat images contaminated by haze. The outcome of the application of VCP appears to be more similar to the reference images compared to HF. Moreover, the Landsat image with VCP haze removal can improve the classification accuracy effectively in comparison to that without haze removal, especially in the cloudy contaminated area

scholarly journals Study of the surface water circulation in San Blas channel (Argentina) using landsat imagery

2011 ◽  
Vol 59 (3) ◽  
pp. 241-252 ◽  
Author(s):  
Débora Beigt ◽  
Diana G. Cuadrado ◽  
María C. Piccolo
Keyword(s):  
Suspended Sediment ◽  
Near Infrared ◽  
Landsat Imagery ◽  
Atmospheric Correction ◽  
Unsupervised Classification ◽  
Water Circulation ◽  
National Commission ◽  
Suspended Sediment Transport ◽  
Landsat Images ◽  
Circulation Patterns

This paper deals with the application of satellite images to study turbidity and water circulation patterns in San Blas channel during a theoretical tidal cycle. Eight Landsat TM and ETM images acquired under clear-sky conditions and representing different tidal stages were selected from a pool of Landsat images provided by the argentinean National Commission of Space Activities (CONAE) and the US Geological Survey. Standard digital image processing techniques were used to perform geometric and radiometric corrections on the visible and near-infrared bands. An image-based atmospheric correction (COST method by CHAVEZ, 1996) was applied. An ISODATA unsupervised classification was performed in order to identify different turbidity levels throughout the channel and adjacent areas. The results suggest that suspended sediment transport towards the channel mouth by ebb currents occurs along both flanks. These currents carry suspended sediment into the open sea, generating an ebb tidal delta which tends to rotate in a clockwise direction. Flood currents trigger turbidity mostly over the southern flank of the channel, generating a flood tidal delta with elongated banks extending in the direction of the tidal currents. From the elongated shape of the turbidity plumes, general tidal circulation patterns were identified.

scholarly journals NEW AUTOMATED CLOUD AND CLOUD-SHADOW DETECTION USING LANDSAT IMAGERY

2014 ◽  
Vol 9 (2) ◽  
Author(s):  
Kustiyo ◽  
Dianovita ◽  
Hedi Ismaya ◽  
Mulia Inda Rahayu ◽  
Erna Sri Adiningsih
Keyword(s):  
Cloud Cover ◽  
Near Infrared ◽  
Landsat Imagery ◽  
Short Wave ◽  
Shadow Detection ◽  
Second Step ◽  
Tropical Region ◽  
Base Method ◽  
Accuracy Result ◽  
Almost All

Cloud cover has become a major problem in the use of optical satellite imageries, particularly in Indonesian region located along equator or tropical region with high cloud cover almost all year round. In this study, a new method for cloud and cloud shadow detection using Landsat imagery for specific Indonesian region was developed to provide a more efficient and effective way to detect clouds and cloud shadows. Landsat Top of Atmosphere (TOA) reflectance and Brightness Temperature (BT) were used as inputs into the model. The first step was to detect cloud based on cloud physical properties using albedo and thermal bands, the second step was to detect cloud shadows using the Near Infrared (NIR), and Short Wave Infrared (SWIR) bands, and finally, the geometric relationships were used to match the cloud and cloud shadow layer, before proceeding to the production of the final cloud and cloud shadow mask. The results were then compared with other method such as tree base cloud separation. It showed that method we proposed could provide better result than tree base method, the accuracy result of this method was 98.75%.

scholarly journals Generation and analysis of a new global burned area product based on MODIS 250 m reflectance bands and thermal anomalies

2018 ◽  
Author(s):  
Emilio Chuvieco ◽  
Joshua Lizundia-Loiola ◽  
M. Lucrecia Pettinari ◽  
Ruben Ramo ◽  
Marc Padilla ◽  
...  
Keyword(s):  
Near Infrared ◽  
Error Rates ◽  
Fire Disturbance ◽  
Spatial Distance ◽  
Burned Area ◽  
Landsat Images ◽  
Thermal Anomalies ◽  
Global Dynamic ◽  
Fire Modelling ◽  
Area Product

Abstract. This paper presents a new global burned area (BA) product, generated from the MODIS red (R) and near infrared (NIR) reflectances and thermal anomalies data, thus providing the highest spatial resolution (approx. 250 m) among the existing global BA datasets. The product includes the full times series (2001–2016) of the MODIS archive. The BA detection 20 algorithm was based on temporal composites of daily images, using temporal and spatial distance to active fires. The algorithm has two steps, the first one aiming to reduce commission errors by selecting the most clearly burned pixels (seeds), and the second one aiming to reduce omission errors by applying contextual analysis around the seed pixels. The product was developed within the European Space Agency's (ESA) Climate Change Initiative programme, under the Fire Disturbance project (Fire_cci). The final output includes two types of BA products: monthly full-resolution continental tiles (http://doi.org/cpk7) and biweekly global grid files at a degraded resolution of 0.25 degrees (http://doi.org/gcx9gf). Each one includes several auxiliary variables that were defined by the climate users to facilitate the ingestion of the product into global dynamic vegetation and emission models. The validation was based on a stratified random sample of 1200 pairs of Landsat images, covering the whole globe from 2003 to 2014. The estimated commission and omission error rates of the pixel product was 0.512 (0.020) and 0.708 (0.030), respectively, lower 30 than previous ESA products but higher than the latest NASA MCD64A1 BA dataset. Examples of potential applications of this product to fire modelling based on burned patches analysis are included in this paper. They show greater sensitivity of our product to small burn patch detection than existing BA products.

scholarly journals Identificación de perturbaciones en el bosque húmedo tropical colombiano usando series temporales de imágenes satelitales Landsat mediante el algoritmo Landtrendr

2019 ◽  
pp. 25
Author(s):  
L. Hurtado ◽  
I. Lizarazo
Keyword(s):  
Time Series ◽  
Vegetation Index ◽  
Near Infrared ◽  
Normalized Difference Vegetation Index ◽  
Forest Disturbance ◽  
Spectral Response ◽  
Short Wave ◽  
Forest Vegetation ◽  
Landsat Images ◽  
Spectral Bands

<p>Time series analysis of satellite images for detection of deforestation and forest disturbances at specific dates has been a subject of research over the last few years. There are many limitations to identify the exact date of deforestation due mainly to the large volume of data and the criteria required for its correct characterization. A further limitation in the analysis of multispectral time series is the identification of true deforestation considering that forest vegetation may undergo different changes over time. This study analyzes deforestation in a zone within the Colombian Amazon using the Normalized Difference Vegetation Index (NDVI) based on semestral median mosaics generated from Landsat images collected from 2000 to 2017. Several samples representing trends of change over the time series were extracted and classified according to their degree of change and persistence in the series, using four categories: (i) deforestation, (ii) degradation, (iii) forest plantation, and (iv) regeneration. Specific deforestation samples were analyzed in the same way using the soil-adjusted vegetation index (SAVI) to reduce the effect of spectral response variations due to soil reflectance changes. It is concluded that the two indices used, together with the near infrared (NIR) and short-wave infrared (SWIR 1) spectral bands, allow to extract values and intervals where the change produced by deforestation on forest vegetation is identified with acceptable accuracy. The analysis of time series using the Landtrendr algorithm confirmed a reliable change detection in each of the forest disturbance categories.</p>

scholarly journals On the possibility of using thermal vision cameras for observations of meteors and other atmospheric formations in long wave infrared

2019 ◽  
pp. 33-38
Author(s):  
P. Kozak ◽  
L. Kozak
Keyword(s):  
Near Infrared ◽  
Low Cost ◽  
Ultra Violet ◽  
Short Wave ◽  
Infrared Observations ◽  
Long Wave ◽  
Thermal Vision ◽  
And Inversion ◽  
The Given ◽  
Long Wave Infrared

The characteristics of the modern low-cost thermal vision cameras for possible observations of meteors and other atmospheric formations in long wave infrared spectrum range of 8-14 μm are investigated. An overview of meteor observations in non-traditional spectrum ranges: ultra-violet, near infrared, short wave, mid wave, and long wave infrared is done. A short description of the modern instruments for infrared observations is presented. By the example of a modern inexpensive model of thermal vision camera of the lower price segment there are presented results of test observations of clouds, possible atmospheric bolide tails and inversion t tracks of airplanes, meteors, and thunderstorm discharges. A short analysis of technical characteristics of the selected model, and corresponding software is given, the merits and demerits of the given type of observational instruments are analyzed as well. The conclusion for outlook of using in the future the thermal vision cameras in meteor astronomy and geophysics is done.

scholarly journals A Multi-Channel Algorithm for Mapping Volcanic Thermal Anomalies by Means of Sentinel-2 MSI and Landsat-8 OLI Data

2019 ◽  
Vol 11 (23) ◽  
pp. 2876 ◽  
Author(s):  
Francesco Marchese ◽  
Nicola Genzano ◽  
Marco Neri ◽  
Alfredo Falconieri ◽  
Giuseppe Mazzeo ◽  
...  
Keyword(s):  
Near Infrared ◽  
Short Wave ◽  
Global Scale ◽  
Landsat 8 ◽  
Thermal Anomalies ◽  
Volcanic Plumes ◽  
Processing Times ◽  
Multi Temporal ◽  
Sentinel 2A ◽  
Sentinel 2

The Multispectral Instrument (MSI) and the Operational Land Imager (OLI), respectively onboard Sentinel-2A/2B and Landsat 8 satellites, thanks to their features especially in terms of spatial/spectral resolution, represents two important instruments for investigating thermal volcanic activity from space. In this study, we used data from those sensors to test an original multichannel algorithm, which aims at mapping volcanic thermal anomalies at a global scale. The algorithm, named Normalized Hotspot Indices (NHI), combines two normalized indices, analyzing near infrared (NIR) and short wave infrared (SWIR) radiances, to identify hotspot pixels in daylight conditions. Results, achieved studying a number of active volcanoes located in different geographic areas and characterized by a different eruptive behavior, demonstrated the NHI capacity in mapping both subtle and more intense volcanic thermal anomalies despite some limitations (e.g., missed detections because of clouds/volcanic plumes). In addition, the study shows that the performance of NHI might be further increased using some additional spectral/spatial tests, in view of a possible usage of this algorithm within a known multi-temporal scheme of satellite data analysis. The low processing times and the straight forth exportability to data from other sensors make NHI, which is sensitive even to other high temperature sources, suited for mapping hot volcanic targets integrating information provided by current and well-established satellite-based volcanoes monitoring systems.

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